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Ice melting probes
(2023)
The exploration of icy environments in the solar system, such as the poles of Mars and the icy moons (a.k.a. ocean worlds), is a key aspect for understanding their astrobiological potential as well as for extraterrestrial resource inspection. On these worlds, ice melting probes are considered to be well suited for the robotic clean execution of such missions. In this chapter, we describe ice melting probes and their applications, the physics of ice melting and how the melting behavior can be modeled and simulated numerically, the challenges for ice melting, and the required key technologies to deal with those challenges. We also give an overview of existing ice melting probes and report some results and lessons learned from laboratory and field tests.
The feasibility study presents results of a hydrogen combustor integration for a Medium-Range aircraft engine using the Dry-Low-NOₓ Micromix combustion principle. Based on a simplified Airbus A320-type flight mission, a thermodynamic performance model of a kerosene and a hydrogen-powered V2530-A5 engine is used to derive the thermodynamic combustor boundary conditions. A new combustor design using the Dry-Low NOx Micromix principle is investigated by slice model CFD simulations of a single Micromix injector for design and off-design operation of the engine. Combustion characteristics show typical Micromix flame shapes and good combustion efficiencies for all flight mission operating points. Nitric oxide emissions are significant below ICAO CAEP/8 limits. For comparison of the Emission Index (EI) for NOₓ emissions between kerosene and hydrogen operation, an energy (kerosene) equivalent Emission Index is used.
A full 15° sector model CFD simulation of the combustion chamber with multiple Micromix injectors including inflow homogenization and dilution and cooling air flows investigates the combustor integration effects, resulting NOₓ emission and radial temperature distributions at the combustor outlet. The results show that the integration of a Micromix hydrogen combustor in actual aircraft engines is feasible and offers, besides CO₂ free combustion, a significant reduction of NOₓ emissions compared to kerosene operation.
Like all preceding transformations of the manufacturing industry, the large-scale usage of production data will reshape the role of humans within the sociotechnical production ecosystem. To ensure that this transformation creates work systems in which employees are empowered, productive, healthy, and motivated, the transformation must be guided by principles of and research on human-centered work design. Specifically, measures must be taken at all levels of work design, ranging from (1) the work tasks to (2) the working conditions to (3) the organizational level and (4) the supra-organizational level. We present selected research across all four levels that showcase the opportunities and requirements that surface when striving for human-centered work design for the Internet of Production (IoP). (1) On the work task level, we illustrate the user-centered design of human-robot collaboration (HRC) and process planning in the composite industry as well as user-centered design factors for cognitive assistance systems. (2) On the working conditions level, we present a newly developed framework for the classification of HRC workplaces. (3) Moving to the organizational level, we show how corporate data can be used to facilitate best practice sharing in production networks, and we discuss the implications of the IoP for new leadership models. Finally, (4) on the supra-organizational level, we examine overarching ethical dimensions, investigating, e.g., how the new work contexts affect our understanding of responsibility and normative values such as autonomy and privacy. Overall, these interdisciplinary research perspectives highlight the importance and necessary scope of considering the human factor in the IoP.
Dieses Lehr- und Fachbuch vermittelt anschaulich die Grundlagen der HF-Technik, gibt konkrete Beschreibungen für den Entwurf von linearen Komponenten aus Bauteilen wie auch Leitungen für High-Speed- und HF-Schaltungen. Dem Leser wird vermittelt, wie Bauteile modelliert und Schaltungen synthetisiert und optimiert werden. Mit Hilfe frei verfügbarer Simulationssoftware können GHz-Schaltungen selbst entwickelt werden. Viele Übungsbeispiele ermöglichen die Eigenkontrolle des Wissensstandes. Weiterhin werden komplexe nichtlineare Komponenten wie Hochfrequenzmischer, Oszillatoren und Synthesegeneratoren in ihrer Funktionalität dargestellt. Die neuen Mixed-Mode-Streuparameter sowie deren Leitungs- und Schaltungstechnik für Anwendungen der schnellen Digital- und der modernen HF-Technik sind ausführlich beschrieben. Es wird auf Systeme für folgende Bereiche eingegangen: Streuparametermesstechnik, verschiedene Funktechniken, UHF-RFID und Lokalisierung- und Ortung. Dem Leser wird somit ermöglicht, komplexe GHz-Schaltungen insbesondere mit Halbleiter-, SMD- und LTCC-Schaltungen zu entwickeln.
Hippocampus
(2023)
Hippocampus – Eine Publikation über das Erscheinungsbild und Verhaltensweisen von Seepferdchen, ihre Lebensräume, Bedrohungen und die Schutzmaßnahmen. Seepferdchen gehören zu den wenigen Fischarten, die allgemein bekannt sind. In den meisten Fällen werden Seepferdchen einfach als »süß« beschrieben. Doch Seepferdchen haben weit mehr zu bieten als ihr märchenhaftes Aussehen. Diese Publikation setzt sich mit kuriosen Erkenntnissen, aktuellen Forschungsergebnissen und Mythen rund um Seepferdchen auseinander und dient als Einstieg in die Thematik.
Extracting workflow nets from textual descriptions can be used to simplify guidelines or formalize textual descriptions of formal processes like business processes and algorithms. The task of manually extracting processes, however, requires domain expertise and effort. While automatic process model extraction is desirable, annotating texts with formalized process models is expensive. Therefore, there are only a few machine-learning-based extraction approaches. Rule-based approaches, in turn, require domain specificity to work well and can rarely distinguish relevant and irrelevant information in textual descriptions. In this paper, we present GUIDO, a hybrid approach to the process model extraction task that first, classifies sentences regarding their relevance to the process model, using a BERT-based sentence classifier, and second, extracts a process model from the sentences classified as relevant, using dependency parsing. The presented approach achieves significantly better resul ts than a pure rule-based approach. GUIDO achieves an average behavioral similarity score of 0.93. Still, in comparison to purely machine-learning-based approaches, the annotation costs stay low.
The integration of high temperature thermal energy storages into existing conventional power plants can help to reduce the CO2 emissions of those plants and lead to lower capital expenditures for building energy storage systems, due to the use of synergy effects [1]. One possibility to implement that, is a molten salt storage system with a powerful power-to-heat unit. This paper presents two possible control concepts for the startup of the charging system of such a facility. The procedures are implemented in a detailed dynamic process model. The performance and safety regarding the film temperatures at heat transmitting surfaces are investigated in the process simulations. To improve the accuracy in predicting the film temperatures, CFD simulations of the electrical heater are carried out and the results are merged with the dynamic model. The results show that both investigated control concepts are safe regarding the temperature limits. The gradient controlled startup performed better than the temperature-controlled startup. Nevertheless, there are several uncertainties that need to be investigated further.
Die Bachelorarbeit „Gemüsevolle Aussichten“ / „Eine bunte Sammlung essbarer Pflanzenteile“ umfasst eine illustrative Auseinandersetzung, bunte Sammlung essbarer Pflanzenteile (Gemüse). Mit ihr entsteht ein visueller Anreiz, sich mehr mit dem gesunden Nahrungsmittel auseinanderzusetzen. Viele Kinder sowie Erwachsene kennen viele Gemüsesorten überhaupt nicht, Gemüse wie z. B. Schwarzwurzeln, Pastinaken oder gar Fenchel ist oftmals wenig bekannt. Mit der Arbeit wird ein informeller, illustrativer Überblick über Gemüse geschaffen, um zum Beispiel auch über die Inhaltsstoffe zu informieren. Denn viele wissen gar nicht, was eigentlich in dem wertvollen Nahrungsmitteln steckt, wie gut ein regelmäßiger Konsum von Gemüse eigentlich für uns ist. Dabei hat der tägliche Konsum von verschiedenen Gemüsesorten nicht nur eine Auswirkung auf die körperliche sondern auch auf die mentale Gesundheit. Viele Gemüsesorten beinhalten bestimmte Vitamine oder weitere Inhaltsstoffe, die sich positiv auf unsere Psyche auswirken und dazu beitragen, zum Bespiel einen depressiven Zustand zu verbessern. Auch die Umwelt kann von einem häufigeren Konsum von Gemüse anstatt Fleisch profitieren. Denn bei der Produktion von Fleisch entsteht viel mehr Kohlenstoffdioxid als bei der Produktion von Gemüse. Auch der Anteil des virtuellen Wassers ist bei der Produktion von Fleisch viel höher. Das Projekt besteht aus einem fadengebundenen Hardcover-Buch und einer Poster-Serie. Zu Beginn der Arbeit wird eine allgemeine Einleitung in das Thema Gemüse gegeben. Im folgenden Hauptteil werden verschiedene Gemüsegruppen und einige der zugehörigen Sorten visuell und informativ erklärt. Bei der Poster-Serie wurden die sechs Hauptfarben, die jeweiligen Gemüseillustrationen separiert und im Stil der Arbeit nummeriert benannt. Mit dem Projekt soll die Unwissenheit über viele Gemüsesorten gesenkt und der Konsum von weniger Fleisch und mehr Gemüse angeregt werden.
Messenger apps like WhatsApp and Telegram are frequently used for everyday communication, but they can also be utilized as a platform for illegal activity. Telegram allows public groups with up to 200.000 participants. Criminals use these public groups for trading illegal commodities and services, which becomes a concern for law enforcement agencies, who manually monitor suspicious activity in these chat rooms. This research demonstrates how natural language processing (NLP) can assist in analyzing these chat rooms, providing an explorative overview of the domain and facilitating purposeful analyses of user behavior. We provide a publicly available corpus of annotated text messages with entities and relations from four self-proclaimed black market chat rooms. Our pipeline approach aggregates the extracted product attributes from user messages to profiles and uses these with their sold products as features for clustering. The extracted structured information is the foundation for further data exploration, such as identifying the top vendors or fine-granular price analyses. Our evaluation shows that pretrained word vectors perform better for unsupervised clustering than state-of-the-art transformer models, while the latter is still superior for sequence labeling.